Climate policies exclusively centered in the Global North harm the economy of the Global South

Policy lessons of a two-region input-output ecological macroeconomic model

Oriol Vallès Codina

2025-11-11

Introduction

Outline

  • ECO-MRIO-SFC modeling as a tool to understand the very complex impact of (carbon) taxes and tariffs on global value chains from a socio-economic perspective: ecological, macroeconomic and distributional implications for class, gender, race / region
  • Trade wars and global value chain fragmentation/regionalization
  • Challenge how to overcome ecological unequal exchange
  • Current model shows ecological and economic impacts are best in cooperative models
  • Implications: competition vs cooperation in trade (Blecker 2025)

Outline

  • Make explicit the military sector (military Keynesianism) and migration as a dynamic feedback
  • Green value chain upgrading from the NZIPL green tech dataset
  • NZIPL net-zero value chain explorer

Motivation: Exchange is Unequal

Starting Point: the JUST2CE project

  • JUST2CE = A Just Transition to the Circular Economy
  • EU-funded project proposing an alternative way of looking at CE
  • Most projects have focused on how to produce circularity. JUST2CE focuses on what (democracy, participation, gender, global justice)
  • Two milestones / WP5 deliverables:
    • Systematic review of macro models assessing CE transition (Fevereiro et al 2025)
    • Formal model(s) to simulate & compare CE policies and transition scenarios (Vallès Codina et al., 2026?)

Systematic Literature Review

Systematic Literature Review (Simplified)

Citation Network of Ecological Macroeconomics

Main Gaps Identified

  • Modelling of Rebound Effects — limited treatment of demand/impact changes via prices, jobs, income
  • Transitional Dynamics — IO analysis typically static
  • Limited Socio-Economic Coverage — often only employment considered
  • Technology Innovation & Diffusion; Demand Assumptions — low-labor-cost tech may be preferred
  • North–South / Core–Periphery Ecological Unequal Exchange (Dorninger 2021, Hickel)

ECO–MRIO–SFC Modeling

The Model: Basic Features

Main tools in (theory-to-data) macroeconomics:

  1. DSGE (and growth) modelsPros: mainstream, simple story. Cons: “small”, unique optimal equilibrium
  2. CGE models (and IAMs)Pros: many variables, cross-industry links. Cons: unique optimal equilibrium, no finance

Cross-breeding two alternatives (Hardt & O’Neill 2017):

  • Leontief IO ModelsPros: many variables, cross-industry links. Cons: static, no finance
  • SFC ModelsPros: dynamics, finance. Cons: homogeneous output

Theoretical Antedecents

  • Increasing use of IO–SFC models; yet none focuses on CE:
  • Berg, Hartley & Richters (2015). A stock-flow consistent input-output model with applications to energy price shocks, interest rates, and heat emissions.
  • Other contributions Naqvi (2015); Naqvi and Stockhammer (2018); Valdecantos & Valentini (2017); Nieto et al (2019); Jackson & Jackson (2021); Cordier et al. (2015); Jackson et al. (2014)
  • MEDEAS, Eurogreen, REAL, ToBe… increasingly very sophisticated one-region models

ECO–MRIO–SFC Model

  1. Two-country macro frame from standard SFC models (Godley & Lavoie 2007):
  • Six sectors: households, production firms, government, commercial banks, central bank
  • Four assets: cash, bank deposits, shares, government bills (+ advances)
  • Only loans to firms (no personal loans)
  • Fixed capital, no inventories
  1. Flexible IO structure: currently 50+ industries
  2. Identification: calibration to target final demand components
  3. Solution: numerical simulations (R), 100 periods, 100 iterations

Final Demand and Gross Output: Constant Sector Shares

Let us consider a \(3\times 3\) production. The final demand vector is:

\[ \mathbf{d} = \begin{bmatrix} \beta_1 \\ \beta_2 \\ \beta_3 \end{bmatrix} c + \begin{bmatrix} \iota_1 \\ \iota_2 \\ \iota_3 \end{bmatrix} i_d + \begin{bmatrix} \sigma_1 \\ \sigma_2 \\ \sigma_3 \end{bmatrix} gov + \begin{bmatrix} \eta_1 \\ \eta_2 \\ \eta_3 \end{bmatrix} exp \]

The gross output vector is:

\[ \mathbf{x} = \mathbf{A} \mathbf{x} + \mathbf{d} = (\mathbf{I}-\mathbf{A})^{-1}\mathbf{d}, \quad \mathbf{A} = \begin{bmatrix} a_{11} & a_{12} & a_{13} \\ a_{21} & a_{22} & a_{23} \\ a_{31} & a_{32} & a_{33} \end{bmatrix} \]

Classical Approach to Prices

For \(i = 1, ..., KN\) commodities where there are \(K\) regions and \(N\) products per region:

\[p = w l + p A (1 + \mu_i) (1 + \kappa_i \delta_i)\]

Isolating prices, \[ p = w l [I - (1 + \mu) (1 + \kappa \delta) A]^{-1} = w l B = w v \]

where \(v \equiv l B\) and the augmented Leontief matrix is

\[B \equiv [I - (1 + \mu) (1 + \kappa \delta) A]^{-1}\]

under uniform profitability rate \(\mu\) and hence different markups.

Carbon Taxation

Carbon taxes are internalized as a production cost for all commodities:

\[p' = p (1 + \tau)\]

where \(p = w l B\) is the price before tax, \(p'\) is the price with tax, and \(\tau\) is the product of emission intensity times the carbon price. In scalar notation, we write \(p_i = w \sum_j l_j b_{ji}\) so that adding the carbon price yields:

\[p'_i = w (1 + \tau_i) \sum_j l_j b_{ji}\]

(Carbon) Tariffs 1

We need to exploit the \(KN \times KN\) dimensionality of global matrix of input-output coefficients \(A\) and thus the augmented Leontief matrix \(B\). For \(K = N = 2\), 2 products and 2 regions, labeled 1 to 4:

\[p = w (l_1, l_2, l_3, l_4) \begin{pmatrix} b_{11} & b_{12} & b_{13} & b_{14} \\ b_{21} & b_{22} & b_{23} & b_{24} \\ b_{31} & b_{32} & b_{33} & b_{34} \\ b_{41} & b_{42} & b_{43} & b_{44} \end{pmatrix}\]

(Carbon) Tariffs 2

In the carbon taxation case, we defined \(1 + \tau\) as a \(KN\)-vector, but it can also be thought of a diagonal matrix with zeros in the off-diagonal. For the tariffs case, operate precisely on the off-diagonal matrices that refer to interregional trade. If region 1 imposes a tariff \((\tau_3, \tau_4)\) on products 1 and 2 of region 2, we multiply coefficients \(b_{ij}\) by \((1 + \tau_i)\) for \(i = 3,4\) and \(j = 1,2\):

\[p' = w (l_1, l_2, l_3, l_4) \begin{pmatrix} b_{11} & b_{12} & b_{13} & b_{14} \\ b_{21} & b_{22} & b_{23} & b_{24} \\ b_{31}(1 + \tau_3) & b_{32}(1 + \tau_3) & b_{33} & b_{34} \\ b_{41}(1 + \tau_4) & b_{42}(1 + \tau_4) & b_{43} & b_{44} \end{pmatrix}\]

Ecological Unequal Exchange: EU (red) vs RoW (green)

Table of Industries

# Industry
1 Agriculture
2 Animal Farming
3 Forestry, logging and related service activities (02)
4 Fishing, operating of fish hatcheries and fish farms; service activities incidental to fishing (05)
5 Extraction of Fossil-Fuels
6 Mining & Quarrying of raw materials
7 Processing of meat
8 Processing of other food & beverage
9 Manufacture of tobacco products (16)
10 Manufacture of textiles
11 Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and plaiting materials (20)
12 Re-processing of secondary wood material into new wood material
13 Pulp
14 Re-processing of secondary paper into new pulp
15 Paper
16 Processing of Fossil Fuels
17 Plastics, basic
18 Re-processing of secondary plastic into new plastic
19 Manufacture of Chemicals
20 Manufacture of rubber and plastic products (25)
21 Manufacture of glass and glass products
22 Re-processing of secondary glass into new glass
23 Manufacture of other non-metallic mineral products
24 Manufacture of cement, lime and plaster
25 Re-processing of ash into clinker
26 Manufacture of Metals
27 Re-processing of Metals
28 Manufacture of durable goods
29 Manufacture of furniture; manufacturing n.e.c. (36)
30 Recycling
31 Production of electricity by fossil fuels
32 Production of electricity by renewable energy
33 Transmission & Distribution
34 Manufacture of gas; distribution of gaseous fuels through mains
35 Water
36 Construction (45)
37 Re-processing of secondary construction material into aggregates
38 Sale, maintenance, repair of motor vehicles, motor vehicle parts, motorcycles, motorcycle parts and accessories
39 Retail sale of automotive fuel
40 Retail & Wholesale trade
41 Leisure Services
42 Transport
43 KIBS
44 Real estate activities (70)
45 Renting of machinery and equipment without operator and of personal and household goods (71)
46 Research and development (73)
47 Public administration and defence; compulsory social security (75)
48 Education (80)
49 Health and social work (85)
50 Incineration of Waste
51 Biogas & Composting
52 Waste water
53 Landfill of Waste
54 Other Services

Modeling Circular Economy Interventions 1: Product Lifetime Extension

Modeling Circular Economy Interventions 2: Resource Efficiency

Results

Balance Sheet

Transaction-Flow Matrix

Multi-Region Input–Output

Calibration

Shocks

Shock
Reduction in Consumption Level
Change in Consumption Composition towards Services
Product Life Time Extension
Higher Recycling Rate
Higher Propensity to Consume Green
Lower Extraction (or Conversion) Rate of Matter
Lower Discarding Rate of Socio-Economic Stock
Higher Renewable Energy Share
Higher Govt Spending towards Efficiency
More Selective Govt Spending towards Recycling Efficiency
More Progressive Taxation

Scenario: Reduction in Consumption Level

Top half

Bottom half

Scenario: Product Lifetime Extension

Impact: Product Lifetime Extension

External Indicators

Social Indicators

Ecological Indicators

Government-led CE Transition

Scenario Summary: Change by Shock, Difference

Top half

Bottom half

Scenario Summary: Change by Shock, Percent

Top half

Bottom half

Future Work

  • Make explicit the military sector (military Keynesianism) and migration as a dynamic feedback
  • Green value chain upgrading from the NZIPL green tech dataset
  • NZIPL Net-Zero Value Chain Explorer

Net-Zero Value Chain Explorer

Sankey Diagram, Solar 2020

Thank you!

oriolvallescodina@gmail.com

ovalles1@jh.edu

References